Figure 3 shows the distribution of climatological
mean sea-air pCO difference
(
pCO
)
during February (Figure 3a) and August (Figure
3b) for the reference year 1995. The yellow-red colors indicate oceanic
areas where there is a net release of CO
to
the atmosphere, and the blue-purple colors indicate regions where there is
a net uptake of CO
.
The equatorial Pacific is a strong source of CO
to
the atmosphere throughout the year as a result of the upwelling and vertical
mixing of deep waters in the central and eastern regions of the equatorial
zone. The intensity of the oceanic release of CO
decreases
westward in spite of warmer temperatures to the west. High levels of CO
are
released in parts of the northwestern subarctic Pacific during the northern
winter and the Arabian Sea in the Indian Ocean during August. Strong convective
mixing that brings up deep waters rich in CO
produces
the net release of CO
in
the subarctic Pacific. The effect of increased DIC concentration surpasses
the cooling effect on pCO
in
seawater during winter. The high pCO
in
the Arabian Sea water is a result of strong upwelling in response to the southwest
monsoon. High pCO
values
in these areas are reduced by the intense primary production that follows the
periods of upwelling.
Figure 3. Distribution of climatological mean sea-air pCO difference
(
pCO
)
for the reference year 1995 representing non-El Niño conditions in February
(a) and August (b). These maps are based on about 940,000 measurements of
surface water pCO
from
1958 through 2000. The pink lines indicate the edges of ice fields. The yellow-red
colors indicate regions with a net release of CO
into
the atmosphere, and the blue-purple colors indicate regions with a net uptake
of CO
from
the atmosphere. The mean monthly atmospheric pCO
value
in each pixel in 1995, (pCO
)air,
is computed using (pCO
)air
= (CO
)air × (Pb
- pH2O). (CO
)air
is the monthly mean atmospheric CO
concentration
(mole fraction of CO
in
dry air) from the GLOBALVIEW
database (2000); Pb is the climatological mean barometric pressure
at sea level from the Atlas
of Surface Marine Data (1994); and the water vapor pressure, pH
O,
is computed using the mixed layer water temperature and salinity from the
World Ocean Database (1998) of NODC/NOAA. The sea-air pCO
difference
values in the reference year 1995 have been computed by subtracting the mean
monthly atmospheric pCO
value
from the mean monthly surface ocean water pCO
value
in each pixel.
The temperate regions of the North Pacific and Atlantic oceans take up a moderate
amount of CO (blue)
during the northern winter (Figure 3a) and release
a moderate amount (yellow-green) during the northern summer (Figure
3b). This pattern is the result primarily of seasonal temperature changes.
Similar seasonal changes are observed in the southern temperate oceans. Intense
regions of CO
uptake
(blue-purple) are seen in the high-latitude northern ocean in summer (Figure
3b) and in the high-latitude South Atlantic and Southern oceans near Antarctica
in austral summer (Figure 3a). The uptake is
linked to high biological utilization of CO
in
thin mixed layers. As the seasons progress, vertical mixing of deep waters
eliminates the uptake of CO
.
These observations point out that the pCO
in
high-latitude oceans is governed primarily by deepwater upwelling in winter
and biological uptake in spring and summer, whereas in the temperate and subtropical
oceans, the
pCO
is
governed primarily by water temperature. The seawater
pCO
is
highest during winter in subpolar and polar waters, whereas it is highest during
summer in the temperate regions. Thus the seasonal variation of
pCO
and
therefore the shift between net uptake and release of CO
in
subpolar and polar regions is about 6 months out of phase with that in the
temperate regions.
The pCO
maps
are combined with the solubility (s) in seawater and the kinetic forcing function,
the gas transfer velocity (k), to produce the flux:
F = k•s•pCO
(1)
The gas transfer velocity is controlled by near-surface turbulence in the liquid boundary layer. Laboratory studies in wind-wave tanks have shown that k is a strong but non-unique function of wind speed. The results from various wind-wave tank investigations and field studies indicate that factors such as fetch, wave direction, atmospheric boundary layer stability and bubble entrainment influence the rate of gas transfer. Also, surfactants can inhibit gas exchange through their damping effect on waves. Since effects other than wind speed have not been well quantified, the processes controlling gas transfer have been parameterized solely with wind speed, in large part because k is strongly dependent on wind, and global and regional wind-speed data are readily available.
Several of the frequently used relationships for the estimation of gas transfer velocity as a function of wind speed are shown in Figure 4 to illustrate their different dependencies. For the Liss and Merlivat (1986) relationship, the slope and intercept of the lower segment was determined from an analytical solution of transfer across a smooth boundary. For the intermediate wind regime, the middle segment was obtained from a field study in a small lake, and results from a wind-wave tank study were used for the high wind regime after applying some adjustments. This relationship is often considered the lower bound of gas transfer-wind speed relationships.
Figure 4. Graph of the different relationships that have been developed
for the estimation of the gas transfer velocity, k, as a function
of wind speed. The relationships were developed from wind-wave tank experiments,
oceanic observations, global constraints and basic theory. The different
forms of the relationships are summarized in Table
1. U is
wind speed at 10 m above the sea surface.
The quadratic relationship of Wanninkhof
(1992) was constructed to follow the general shape of curves derived
in wind-wave tanks but adjusted so that the global mean transfer velocity
corresponds with the long-term global average gas transfer velocity determined
from the invasion of bomb C
into the ocean. Because the bomb
C
is also used as a diagnostic or tuning parameter in global ocean biogeochemical
circulation models, this parameterization yields internally consistent results
when used with these models, making it one of the more favored parameterizations.
Using the same long-term global C
constraint but basing the general shape of the curve on recent CO
flux
observations over the North Atlantic determined using the covariance technique, Wanninkhof
and McGillis (1999) proposed a significantly stronger (cubic) dependence
with wind speed. This relationship shows a weaker dependence on wind for wind
speeds less than 10 ms
and
a significantly stronger dependence at higher wind speeds. However, the relationship
is not well constrained at high wind speeds because of the large scatter in
the scarce observations. Both the U
and
U
relationships
fit within the data envelope of the study, but the U
relationship
provides a significantly better fit. Nightingale
et al. (2000) determined a gas exchange-wind speed relationship based on
the results of a series of experiments utilizing deliberately injected sulfur
hexafluoride (SF
),
He
and non-volatile tracers performed in the last decade.
The global oceanic CO uptake
using different wind speed/gas transfer velocity parameterizations differs
by a factor of three (Table 1). The wide range
of global CO
fluxes
for the different relationships illustrates the large range of results and
assumptions that are used to produce these relationships. Aside from differences
in global oceanic CO
uptake,
there are also significant regional differences. Figure
5 shows that the relationship of W&M-99 yields systematically lower
evasion rates in the equatorial region and higher uptake rates at high latitudes
compared with W-92, leading to significantly larger global CO
uptake
estimates.
Figure 5. Effects of the various gas transfer/wind speed relationships
on the estimated air-sea exchange flux of CO in
the ocean as a function of latitude. The global effects on the net air-sea
flux are given in Table 1.
In addition to the non-unique dependence of gas exchange on wind speed, which
causes a large spread in global air-sea CO flux
estimates, there are several other factors contributing to biases in the results.
Global wind-speed data obtained from shipboard observations, satellites and
data assimilation techniques show significant differences on regional and global
scales. Because of the non-linearity of the relationships between gas exchange
and wind speed, significant biases are introduced in methods of averaging the
product of gas transfer velocity and wind speed. The common approach of averaging
the
pCO
and k separately
over monthly periods, determining the flux from the product and ignoring the
cross product leads to a bias that is about 0.2 to 0.8 Pg C yr
lower
in the global uptake estimate. This bias shows a regional variation that is
dependent on the distribution and magnitude of winds. This issue has been partly
rectified in some of the relationships in which a global wind-speed distribution
is used to create separate relationships between gas transfer and wind speed
for short-term (a day or less) and long-term (a month or more) periods. Since
wind-speed distributions are regionally dependent and vary on time scales of
hours, this approach is far from perfect.
The groundwork of efforts laid over the past decade and recently improved
technologies make the quantification of regional and global CO fluxes
a more tractable problem now. Satellites equipped with scatterometers that
are used to determine wind speed offer daily global coverage. Moreover, these
instruments measure sea-surface roughness that is directly related to gas transfer.
This remotely sensed information, along with regional statistics of wind-speed
variability on time scales shorter than a day, offers the real possibility
that more accurate gas transfer velocities will be obtained. Efforts are underway
to increase the coverage of pCO
through
more frequent measurements and data assimilation techniques, again utilizing
remote sensing of parameters such as sea-surface temperature and wind speed.
Better quantification of the fluxes will lead to better boundary conditions
for models and improved forecasts of atmospheric CO
concentrations.
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